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Updated: Oct 7, 2025

Assessment of Social Transmission of Food Preferences Behaviors
Published on: January 25, 2018
Associations between the fast-food environment and diabetes prevalence in the Netherlands: a cross-sectional study
Anna-Maria Ntarladima1, Derek Karssenberg2, Maartje Poelman3
1Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, Netherlands; Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, Netherlands; Global Geo Health Data Center, Utrecht University, Utrecht, Netherlands; Urban Geographies, Amsterdam Institute for Social Science Research, University of Amsterdam, Amsterdam, Netherlands.
Background:
Diabetes is a major health concern and is influenced by lifestyle, which can be affected by the neighbourhood environment. Specifically, a fast-food environment can influence eating behaviours and thus diabetes prevalence. Therefore, our aim was to assess the relationship between fast-food environment and diabetes prevalence for urban and rural environments in the Netherlands, using multiple indicators and buffer sizes.
Methods:
In this cross-sectional study, data on a nationwide sample of adults older than 19 years in the Netherlands were taken from the 2012 Dutch national health survey (from Public Health Monitor), in which participants were surveyed on topics related to health and lifestyle behaviour. Fast-food outlet exposures were determined within street-network buffers of 100 m, 400 m, 1000 m, and 1500 m around residential addresses. For each of these buffers, three indicators were calculated: presence (yes or no) of fast-food outlets, fast-food outlet density, and ratio. Logistic regression analyses were carried out to assess associations of these indicators with diabetes, adjusting for potential confounders and stratifying into urban and rural areas.
Findings:
387 195 adults were surveyed, 284 793 of whom were included in the study. 22 951 (8%) reported having diabetes. Fast-food outlet exposures were positively associated with diabetes prevalence. We did not observe large differences between urban and rural areas. The effect estimates were small for all indicators. For example, in the 400 m buffer in the urban environment, the odds ratio (OR) for having diabetes among people with a fast-food outlet present compared with those without, was 1·006 (95% CI 1·003-1·009) using the presence indicator. The presence indicator showed higher effect estimates and the most consistent results across buffer sizes (ranging from OR 1·005 [95% CI 1·000-1·010] with the 1000 m buffer to 1·016 [1·005-1·028] with the 1500 m buffer in urban areas and from 1·002 [0·998-1·005] with the 1500 m buffer to 1·009 [1·006-1·018] with the 100 m buffer in rural areas) compared with the density and ratio indicators.
Interpretation:
The results confirm the evidence that the fast-food outlet environment is a diabetes risk factor. All data included were at the individual level and the variability was ensured by the spatial distribution and number of participants. In this study, we only accounted for residential exposure because we were unable to account for exposure outside the residential environment. The findings of this study encourage local governments to consider the potential adverse effects of fast-food exposures and aim at minimising unhealthy food access.
Funding:
Global Geo Health Data Centre, Utrecht University, Netherlands.
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